In this talk, I will present the main ideas behind the development of a methodology for engineering distributed systems capable of some cognitive processing ability, such as collective decision making. I will move from theoretical studies of collective decision in distributed systems, which support the identification of the causal relationship between microscopic mechanisms and macroscopic patterns. Such theoretical understanding must be translated into formal methods and guidelines for engineering artificial systems (e.g., the interactions observed between bees during nest site selection can be distilled into a methodology for optimal decision making in swarm robotics systems). In this respect, I will introduce the concept of cognitive design patterns, that is, general solutions for the design of distributed cognitive systems, and will discuss the example of collective decisions through a simple case study.
Dr. Vito Trianni is a tenured researcher at the Institute of Cognitive Sciences and Technology of the Italian National Research Council (CNR-ISTC). He owns a Ph.D. in Applied Sciences delivered by the Université Libre de Bruxelles in 2006, and a MSc in Computer Science Engineering delivered by Politecnico di Milano in 2000. He published more than 60 papers in international journals and peer-reviewed conference proceedings, with an overall H-Index of 21 according to Google Scholar. His main research interests are in swarm intelligence and swarm robotics, and the relationship between collective behaviour and cognition. Dr. Trianni participated to some of the most successful EU projects in cognitive systems and robotics (Swarm-bots, ECAgents, Swarmanoid), and features thorough expertise, both theoretical and experimental, in the design and analysis of collective and self-organising behaviours, especially applied to swarm robotics systems. Recently, given the lack of systematic methodologies that can guide the experimental design, Dr. Trianni started to formalise an engineering approach for the synthesis of collective behaviours, through evolutionary techniques and swarm intelligence design methods. Besides engineering robotic systems, Dr. Trianni’s research activities instantiate a synthetic approach to the understanding of distributed cognition in natural systems.